Member of Technical Staff: Application Engineer WibiData
Type: Full Time
Min. Experience: Mid Level
MTS: Application Engineer
WibiData, Inc. is looking for a hard-working, intelligent, and well-rounded engineer with a can-do attitude to help our growing company. The ideal applicant shares our love of technology and data-driven decision-making and understands that people are our most valuable asset. We have a simultaneously fun and hard-working office environment and love to bring on new team members who see a future for themselves with the WibiData team. We prioritize hiring overqualified candidates enthusiastic about helping in areas outside of the job description, and who will be ready and able to take on new roles as they become available.
Application Engineers at WibiData work closely with our field and platform engineering teams to build Big Data Applications. WibiData Application Engineers build revolutionary Big Data Applications on top of our open-source Kiji Project using a variety of tools such as Hadoop, HBase, Java, Scala, data structures, algorithms and software design. These applications integrate easily with a wide variety of existing application channels such as websites, mobile app servers, e-mail marketing systems, advertising networks and operational financial systems. Applications are also highly customizable and pluggable, allowing our customers to adapt them for specific use cases. WibiData Application Engineers enjoy developing business applications, gluing infrastructure components together, and integrating a variety of systems to solve hard problems such as product recommendations for retailers, load default predictions and behavioral fraud detection for banks, and targeting, localization and content personalization for mobile application providers.
Languages we like: Java, Scala, Ruby, Python, JS, CSS
Prior experience with full-stack web application development encouraged
Prior experience with Hadoop, HBase, Cassandra, BigTable, or other NoSQL datastores a plus
Prior experience with personalization, recommendation systems, and machine learning a plus
||San Francisco, CA |